Soil salinity detection index using shortwave infrared bands. Effective for identifying salt-affected soils and monitoring soil degradation in arid regions.

Used in crop monitoring, and mineral exploration.

When to use

  • Mineral exploration target identification in arid and bare-ground regions
  • Hydrothermal alteration zone mapping
  • Lithological unit discrimination
  • Iron oxide and clay mineral mapping
  • Pre-field reconnaissance for geological surveys
  • Soil Salinity Detection
  • Soil Quality Assessment

Limitations

  • Vegetation cover masks underlying mineral signatures — works best on bare ground
  • Atmospheric water vapour absorbs in similar SWIR regions, requiring correction
  • Particle size and mineral mixtures produce non-linear spectral mixing
  • Should be combined with field validation — single-index identification is unreliable
  • Different mineral assemblages can produce similar spectral signatures
  • Requires sensors with SWIR bands — not available on all platforms

General Formula

SWIR1 1600-1700 nm
SWIR2 2145-2185 nm

Sensor-Specific Formulas

Most-used sensors — click to show code below

SensorProviderFormulaBand Mapping
USGS/NASA(B6 - B7) / (B6 + B7)SWIR1→B6, SWIR2→B7
ESA(B11 - B12) / (B11 + B12)SWIR1→B11, SWIR2→B12
MAXAR(SWIR3 - SWIR5) / (SWIR3 + SWIR5)SWIR1→SWIR3, SWIR2→SWIR5

Spectral Band Visualization — Landsat 8/9

Code Examples

Adapted for Landsat 8/9 bands —

ndsi_landsat-8-9.py

Frequently Asked Questions

What is the NDSI (Normalized Difference Salinity Index) and when should I use it?

Soil salinity detection index using shortwave infrared bands. Effective for identifying salt-affected soils and monitoring soil degradation in arid regions. Geological indices identify mineral compositions and lithological features by targeting diagnostic absorption features in shortwave infrared wavelengths. Different minerals produce unique spectral signatures that these indices isolate. NDSI is particularly suited for soil salinity detection, soil quality assessment, agricultural land management. The general formula is (SWIR1 - SWIR2) / (SWIR1 + SWIR2), which requires SWIR1 and SWIR2 spectral bands.

Which satellite sensors can I use to calculate NDSI?

NDSI is supported by 3 satellite sensors in our database, including Landsat 8/9, Sentinel-2, WorldView 3. Each sensor uses different band designations — for example, Landsat 8/9 uses the formula (B6 - B7) / (B6 + B7), while Sentinel-2 uses (B11 - B12) / (B11 + B12). Select a sensor above to see its specific band mapping.

What spectral bands does NDSI require and why?

NDSI requires SWIR1 (1600-1700 nm), SWIR2 (2145-2185 nm). These specific wavelength regions correspond to diagnostic mineral absorption features caused by electronic transitions and vibrational overtones in crystal lattices.

How do I calculate NDSI in Python or R?

Both Python and R code samples are provided above. In Python, use rasterio to load individual band GeoTIFF files and numpy for the arithmetic. In R, the terra package handles raster operations efficiently. The key is to load bands as floating-point arrays to avoid integer division, and to handle division-by-zero cases where the denominator equals zero. For production use, consider applying a valid data mask to exclude no-data pixels before calculation.

What minerals can NDSI help identify?

Soil salinity detection index using shortwave infrared bands. Effective for identifying salt-affected soils and monitoring soil degradation in arid regions. For accurate mineral identification, this index should be used alongside other geological indices and validated with field samples or known geology maps. Spectral unmixing or supervised classification using multiple indices typically yields more reliable results than any single index alone.

NDSI vs other geology indices

IndexNameHow it differs
AKPAlunite/Kaolinite/Pyrophylite IndexAlternative geology index — different band combination
ALTAlteration IndexAlternative geology index — different band combination
AMPAmphibole IndexAlternative geology index — different band combination
ClayClay IndexAlternative geology index — different band combination

Related Geology Indices

References

Khan et al. (2005)

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